Feature extraction and selection from speech impart great importance in successfully identifying emotional states. However, selecting a large number of features breeds various complexities, which eventually results in classification error [1]}, [2]}. On the other hand, the influence of language makes speech emotion recognition ambiguous. Languages can differ in many ways with regards to their grammatical and morphological properties [2]}. The variations in dialects of a language can occur due to the usage of words, accents, or how people arrange their speech. This can be credited to certain social factors, culture, or geographical distance [4]}. So it becomes essential for us to work with vocal features which are independent of the nuances of language. Therefore in this study, we aim to explore if speech emotion recognition is independent of language by selecting language-independent vocal features.
